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About the Role

We are seeking a Data Engineer to develop the technical vision, architectural design, and implementation of our AI-enabling data ecosystem. In this strategic role, you will bridge the gap between traditional enterprise data architecture and modern AI capabilities. You will design resilient, scalable data pipelines, and real-time streaming architectures that power LLM workflows, Retrieval-Augmented Generation (RAG) pipelines, and predictive ML models. You will work closely with Data Scientists, Analysts, and other Engineers to establish best-in-class data engineering practices for traditional and AI enabled workloads.

Responsibilities

Architect, build, and scale clean, reliable, and latency-optimized data pipelines (batch and real-time) designed specifically to supply structured, semi-structured, and unstructured data to AI/ML applications and Large Language Models (LLMs).
Contribute to defining the architectural blueprint for the Top of House AI data layer. Serve as a hands-on technical lead, guiding junior and mid-level engineers in coding standards, design patterns, and engineering excellence.
Partner with Enterprise Security and Data Governance teams to implement robust data classification, privacy safeguards, and automated lineage tracking for AI models and training datasets.
Build and maintain scalable feature stores to support both real-time inferencing and offline model training across executive-facing predictive models.
Audit and optimize cross-cloud data pipelines, query performance, and storage infrastructure for efficiency, cost management, and reliability.
Partner directly with Technical Program Managers, Data Scientists, Top of House leads, and C-suite stakeholders to turn executive data needs into production-ready solutions.

Requirements

Bachelor's Degree or higher in Computer Science or a related quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Engineering)
At least 6 years of experience in application development (Internship experience does not apply)
At least 4 years of experience in distributed data
At least 4 years of experience with SQL
At least 4 years of experience programming with at least one of the following languages: Python, Java, or Scala
At least 4 years of experience designing and developing data pipelines
At least 2 years of experience in data modeling and designing end-to-end data solutions using both relational and non-relational database systems
Master's Degree in a related field
9+ years of experience in application development including Python, SQL, Scala, or Java
5+ years of experience with a public cloud (AWS, Microsoft Azure, Google Cloud)
5+ year experience working on real-time data and streaming applications
5+ years of data warehousing experience (eg Snowflake)
Experience leveraging interactive AI tooling to accelerate productivity, utilizing capabilities beyond basic code completion (Claude, Gemini)

Skills

Python
SQL
Databricks
Snowflake
AI
LLM
RAG
ML
Data Engineering
Data Modeling
AWS
Microsoft Azure
Google Cloud
Real-time data
Streaming applications
Data warehousing

Location

McLean, VA
New York, NY
Plano, TX
Richmond, VA
Riverwoods, IL

Work Type

Full-time

Experience Level

6+ years of experience in application development
4+ years of experience in distributed data
4+ years of experience with SQL
4+ years of experience programming with Python, Java, or Scala
4+ years of experience designing and developing data pipelines
2+ years of experience in data modeling
9+ years of experience in application development
5+ years of experience with a public cloud
5+ years experience working on real-time data and streaming applications
5+ years of data warehousing experience

Education Level

Bachelor's Degree in Computer Science or a related quantitative field
Master's Degree in a related field

Salary/Compensations

McLean, VA: $229,900 - $262,400
New York, NY: $250,800 - $286,200
Plano, TX: $209,000 - $238,500
Richmond, VA: $209,000 - $238,500
Riverwoods, IL: $209,000 - $238,500

Benefits

Comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being.

About the Company

The Enterprise Platforms Tech Top of House Data & Analytics team serves as the strategic intelligence backbone for executive leadership and strategy.
We operate at the intersection of business strategy, core enterprise infrastructure, and advanced analytics.
Our team is responsible for delivering high-impact, enterprise-level data products, decisioning engines, and modern analytics capabilities that power executive level decision-making.

Equal Opportunity

Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws.
Capital One promotes a drug-free workplace.
Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City’s Fair Chance Act; Philadelphia’s Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.